지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.17 No.2
- 발행연도
- 2017.6
- 수록면
- 82 - 90 (9page)
- DOI
- 10.5391/IJFIS.2017.17.2.82
이용수
초록· 키워드
오류제보하기
Vessel Traffic Services operators have kept sharp monitoring and provided the appropriate information to ensure safe and effective navigation. While attending the tasks, analysis of traffic patterns and navigational data is required to conduct accurate situation assessment in decision-making process of VTS operators (VTSO). Unfortunately, there are problems in the process of data analysis such as appropriateness of time, VTSO’s personal error and improper judgment. Therefore, objective and proper data analysis is necessary to solve above matters. However, it is virtually impossible to monitor all vessels because there are many vessels in the VTS area and at the same time complex traffic situations are produced. In this study, we proposed a machine learning algorithms for objective and accurate pattern recognition and data modeling. Support Vector Regression algorithm was used for data learning and modeling. The optimal parameters were selected through v-fold cross validation and grid search. The machine learning was conducted with virtual route and ship tracks that are similar with real navigational environment. As a result, we presented reference route and navigational patterns. We expect that the proposed modeling methods could be utilized for relevant tasks as the useful information to VTSO and/or ship’s mater.
목차
Abstract
1. Introduction
2. Modeling Methods
3. Simulation
4. Data Learning
5. Conclusion
References
참고문헌 (22)
참고문헌 신청
J. S. Kim, J. S. Jeong, and G. K. Park, “Prediction table for marine traffic for vessel traffic service based on cognitive work analysis,” International Journal of Fuzzy Logic and Intelligent Systems, vol. 13, no. 4, pp. 315-323, 2013. http://dx.doi.org/10.5391/ijfis.2013.13.4.315
J. S. Kim, J. S. Jeong, and G. K. Park, “Utilization of planned routes and dead reckoning positions to improve situation awareness at sea,” International Journal of Fuzzy Logic and Intelligent Systems, vol. 14, no. 4, pp. 288-294, 2014. http://dx.doi.org/10.5391/ijfis.2014.14.4.288
International Maritime Organization, Strategy for the Development and Implementation of e- Navigation (MSC85-report, Annexes 20 and 21). Available http://www.imo.org/en/OurWork/Safety/Navigation/Documents/enavigation/MSC%2085%20-%20annex%2020%20-%20Strategy%20for%20the%20development%20and%20implementation%20of%20enav.pdf
T. Hong, “Development of a system for transmitting a navigator’s intention for safe navigation,” International Journal of Fuzzy Logic and Intelligent Systems, vol. 14, no. 2, pp. 130-135, 2014. http://dx.doi.org/10.5391/ijfis.2014.14.2.130
International Maritime Organization, Guidelines for Vessel Traffic Services (Resolution A.857(20)), International Maritime Organization, London, UK, 1997. Available http://www.maritime-vts.co.uk/A857.pdf
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UCI(KEPA) : I410-ECN-0101-2018-003-001014426